Method and system for prioritizing control strategies minimizing real time energy consumption of built environment

ABSTRACT

The present disclosure provides a computer-implemented method for prioritizing one or more instructional control strategies to reduce time-variant energy demand of a built environment associated with renewable energy sources. The computer-implemented method includes collection of a first set of statistical data, fetching of a second set of statistical data, accumulation of a third set of statistical data, reception of a fourth set of statistical data and gathering of fifth set of statistical data. Further, the computer-implemented method includes parsing and comparison of the first set of statistical data, the second set of statistical data, the third set of statistical data, the fourth set of statistical data and the fifth set of statistical data. In addition, the computer-implemented method includes identification and prioritization of one or more instructional control strategies to reduce the time-variant energy demand associated with the built environment.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/590,150, filed on May 9, 2017, entitled “METHOD AND SYSTEM FORPRIORITIZING CONTROL STRATEGIES MINIMIZING REAL TIME ENERGY CONSUMPTIONOF BUILT ENVIRONMENT,” which claims the benefit under 35 U.S.C. § 119(e)of the filing date of U.S. Provisional Patent Application No.62/334,367, filed on May 10, 2016, entitled “METHOD AND SYSTEM FORREDUCING THE ENERGY DEMAND OF A BUILDING OR GRID NETWORK.” Thedisclosures of the above applications are incorporated by reference intheir entireties as a part of this document.

TECHNICAL FIELD

The present disclosure relates to a field of energy management system.More specifically, the present disclosure relates to a method and systemfor prioritizing instructional control strategies affecting operationalbehavior and states of a plurality of energy consuming devices andreducing time-variant energy demand of one or more built environments.

BACKGROUND

Over the last few decades, increasing population and energy requirementsto power modern transportation and electronic technologies result in arapid development in energy generation and distribution technology. Inorder to meet the energy generation and distribution requirements,energy utilities depend mostly on the non-renewable energy sources likefossil fuels which produce a high amount of carbon emissions. Refinementprocesses of fossil fuels and/or its by-products and their combustion todrive electric generators have contributed as one of the major cause ofexcessive carbon emissions. The release of carbon and other chemicalby-products into the atmosphere has impacted temperatures and climatepatterns on a global scale. The increased awareness of the impacts ofcarbon emissions from the use of fossil fueled electric generation alongwith the increased cost of producing high power during peak loadconditions has increased the need for alternative solutions. Thesealternative solutions are referred to as renewable energy sources, whichmay be used to generate electricity. These renewable energy sources maybe applied to electric drive trains, electric automation andtransportation, without the need to extract, transport, refine, combust,and release carbon-based fossil fuels. Renewable energy comes in manyforms, but significantly is generated by capturing energy from natural,non-carbon intensive sources such as wind, sunlight, water movement,geothermal and other new sources as they are discovered and improved.Unlike fossil fuels and/or its by-products, these renewable energysources are complex in nature as they are intermittent and cannot becontrolled actively by humans. This enhances the probability ofoccurrence of certain time periods where power production far exceedsdemands or certain time periods where power production falls short ofdemands. This creates major challenges for energy utilities to makeinvestments, generate power for sale and profit. Also, this createsmajor challenges for the markets in establishing a price of energy forconsumers. Nowadays, energy storage means are deployed to store energywhen power production is excessive and release energy when demandsexceed power production output. These energy storage means include butmay not be limited to batteries and sophisticated power banks. However,there are many limitations to the effective installation of the energystorage means due to sizing requirements, specific load profiles andother attributes which must be matched very carefully in order toprovide feasible economic returns.

SUMMARY

In a first example, a computer-implemented method is provided. Thecomputer-implemented method prioritizes one or more instructionalcontrol strategies affecting operational behavior and states of aplurality of energy consuming devices. In addition, thecomputer-implemented method reduces time-variant energy demand of one ormore built environments associated with renewable energy power sources.The computer-implemented method may include a first step of collectionof a first set of statistical data associated with an energy consumptionof a plurality of energy consuming and control devices present in eachof the one or more built environments. In addition, thecomputer-implemented method may include a second step of fetching asecond set of statistical data associated with an occupancy behavior ofa plurality of users present inside each of the one or more builtenvironment. Moreover, the computer-implemented method may include athird step of accumulation of a third set of statistical data associatedwith each of a plurality of energy storage and supply means. Further,the computer-implemented method may include a fourth step of receptionof a fourth set of statistical data associated with each of a pluralityof environmental sensors present inside or outside the one or more builtenvironments. Furthermore, the computer-implemented method may include afifth step of gathering a fifth set of statistical data associated witheach of a plurality of energy pricing models. Also, thecomputer-implemented method may include a sixth step of parsing thefirst set of statistical data, the second set of statistical data, thethird set of statistical data, the fourth set of statistical data andthe fifth set of statistical data. The parsing may be done bydevelopment of an energy usage profile of each category of energyconsuming devices, each user of the plurality of users, each floor of abuilt environment and each of the one or more built environments. Inaddition, the computer-implemented method may include a seventh step ofcomparison of the energy usage profile associated with the plurality ofenergy consuming devices, the plurality of users, each floor and each ofthe one or more built environments. Moreover, the computer-implementedmethod may include an eighth step of identification of a set of controlstrategies and key performance indicators. Further, thecomputer-implemented method may include a ninth step of prioritizationof one or more instructional control strategies from the set of controlstrategies affecting operational behavior and states of a type of energyconsuming device over one or more types of energy consuming devices forreducing time-variant energy demand. The first set of statistical datamay include a current operational state data and a past operationalstate data associated with the energy consuming devices. The first setof statistical data may be gathered by one or more energy meteringdevices installed in each of the one or more built environments. Thefirst set of statistical data may be gathered based on a first pluralityof parameters. The first plurality of data may be gathered in real time.The second set of statistical data may include a first plurality ofoccupancy data and a second plurality of occupancy data. The firstplurality of occupancy data may be associated with energy consumptionbehavior of each of a plurality of users present inside the one or morebuilt environments. The second plurality of occupancy data may beassociated with an occupancy pattern of each of the plurality of userspresent inside the one or more built environments. The third set ofstatistical data may include a current and historical energy storage andsupply capacity data associated with the plurality of energy storage andsupply means. The third set of statistical data may be accumulated basedon a second plurality of parameters. The third set of statistical datamay be accumulated in the real time. The fourth set of statistical datamay include a current and historical environmental condition data of atleast one of inside and outside of the one or more built environments.The fourth set of statistical data may be received based on a thirdplurality of parameters. The fourth set of statistical data may bereceived in the real time. The fifth set of statistical data may includecurrent and historical recordings of energy pricing state affecting theone or more built environments. The fifth set of statistical data may begathered based on a fourth plurality of parameters. The fifth set ofstatistical data may be gathered in the real time. The comparison may beperformed for segregation of each of the one or more built environmentsbased on surplus and shortage of energy demand and supply correspondingto the built environment of the one or more built environments. The setof control strategies may be identified for regulation of the firstplurality of parameters associated with the plurality of energyconsuming devices and the second plurality of parameters associated withthe plurality of energy storage and supply means. The key performanceindicators may be identified corresponding to one or more levels ofcontrol associated with the set of control strategies. The keyperformance indicators may be identified based on operating behavior andstates of each of the plurality of energy consuming devices. Theidentification may be performed in real time. The one or moreinstructional control strategies may be prioritized to achieve the oneor more levels of control. The set of control strategies may include aplurality of operational and non-operational instructions.

In a second example, a computer system is provided. The computer systemmay include one or more processors and a memory coupled to the one ormore processors. The memory may store instructions which, when executedby the one or more processors, may cause the one or more processors toperform a method. The method prioritizes one or more instructionalcontrol strategies affecting operational behavior and states of aplurality of energy consuming devices. In addition, the method reducestime-variant energy demand of one or more built environments associatedwith renewable energy power sources. The method may include a first stepof collection of a first set of statistical data associated with anenergy consumption of a plurality of energy consuming and controldevices present in each of the one or more built environments. Inaddition, the method may include a second step of fetching a second setof statistical data associated with an occupancy behavior of a pluralityof users present inside each of the one or more built environment.Moreover, the method may include a third step of accumulation of a thirdset of statistical data associated with each of a plurality of energystorage and supply means. Further, the method may include a fourth stepof reception of a fourth set of statistical data associated with each ofa plurality of environmental sensors present inside or outside the oneor more built environments. Furthermore, the method may include a fifthstep of gathering a fifth set of statistical data associated with eachof a plurality of energy pricing models. Also, the method may include asixth step of parsing the first set of statistical data, the second setof statistical data, the third set of statistical data, the fourth setof statistical data and the fifth set of statistical data. The parsingmay be done by development of an energy usage profile of each categoryof energy consuming devices, each user of the plurality of users, eachfloor of a built environment and each of the one or more builtenvironments. In addition, the method may include a seventh step ofcomparison of the energy usage profile associated with the plurality ofenergy consuming devices, the plurality of users, each floor and each ofthe one or more built environments. Moreover, the method may include aneighth step of identification of a set of control strategies and keyperformance indicators. Further, the method may include a ninth step ofprioritization of one or more instructional control strategies from theset of control strategies affecting operational behavior and states of atype of energy consuming device over one or more types of energyconsuming devices for reducing time-variant energy demand. The first setof statistical data may include a current operational state data and apast operational state data associated with the energy consumingdevices. The first set of statistical data may be gathered by one ormore energy metering devices installed in each of the one or more builtenvironments. The first set of statistical data may be gathered based ona first plurality of parameters. The first plurality of data may begathered in real time. The second set of statistical data may include afirst plurality of occupancy data and a second plurality of occupancydata. The first plurality of occupancy data may be associated withenergy consumption behavior of each of a plurality of users presentinside the one or more built environments. The second plurality ofoccupancy data may be associated with an occupancy pattern of each ofthe plurality of users present inside the one or more builtenvironments. The third set of statistical data may include a currentand historical energy storage and supply capacity data associated withthe plurality of energy storage and supply means. The third set ofstatistical data may be accumulated based on a second plurality ofparameters. The third set of statistical data may be accumulated in thereal time. The fourth set of statistical data may include a current andhistorical environmental condition data of at least one of inside andoutside of the one or more built environments. The fourth set ofstatistical data may be received based on a third plurality ofparameters. The fourth set of statistical data may be received in thereal time. The fifth set of statistical data may include current andhistorical recordings of energy pricing state affecting the one or morebuilt environments. The fifth set of statistical data may be gatheredbased on a fourth plurality of parameters. The fifth set of statisticaldata may be gathered in the real time. The comparison may be performedfor segregation of each of the one or more built environments based onsurplus and shortage of energy demand and supply corresponding to thebuilt environment of the one or more built environments. The set ofcontrol strategies may be identified for regulation of the firstplurality of parameters associated with the plurality of energyconsuming devices and the second plurality of parameters associated withthe plurality of energy storage and supply means. The key performanceindicators may be identified corresponding to one or more levels ofcontrol associated with the set of control strategies. The keyperformance indicators may be identified based on operating behavior andstates of each of the plurality of energy consuming devices. Theidentification may be performed in real time. The one or moreinstructional control strategies may be prioritized to achieve the oneor more levels of control. The set of control strategies may include aplurality of operational and non-operational instructions.

In a third example, a computer-readable storage medium is provided. Thecomputer-readable storage medium encodes computer executableinstructions that, when executed by at least one processor, performs amethod. The method prioritizes one or more instructional controlstrategies affecting operational behavior and states of a plurality ofenergy consuming devices. In addition, the method reduces time-variantenergy demand of one or more built environments associated withrenewable energy power sources. The method may include a first step ofcollection of a first set of statistical data associated with an energyconsumption of a plurality of energy consuming and control devicespresent in each of the one or more built environments. In addition, themethod may include a second step of fetching a second set of statisticaldata associated with an occupancy behavior of a plurality of userspresent inside each of the one or more built environment. Moreover, themethod may include a third step of accumulation of a third set ofstatistical data associated with each of a plurality of energy storageand supply means. Further, the method may include a fourth step ofreception of a fourth set of statistical data associated with each of aplurality of environmental sensors present inside or outside the one ormore built environments. Furthermore, the method may include a fifthstep of gathering a fifth set of statistical data associated with eachof a plurality of energy pricing models. Also, the method may include asixth step of parsing the first set of statistical data, the second setof statistical data, the third set of statistical data, the fourth setof statistical data and the fifth set of statistical data. The parsingmay be done by development of an energy usage profile of each categoryof energy consuming devices, each user of the plurality of users, eachfloor of a built environment and each of the one or more builtenvironments. In addition, the method may include a seventh step ofcomparison of the energy usage profile associated with the plurality ofenergy consuming devices, the plurality of users, each floor and each ofthe one or more built environments. Moreover, the method may include aneighth step of identification of a set of control strategies and keyperformance indicators. Further, the method may include a ninth step ofprioritization of one or more instructional control strategies from theset of control strategies affecting operational behavior and states of atype of energy consuming device over one or more types of energyconsuming devices for reducing time-variant energy demand. The first setof statistical data may include a current operational state data and apast operational state data associated with the energy consumingdevices. The first set of statistical data may be gathered by one ormore energy metering devices installed in each of the one or more builtenvironments. The first set of statistical data may be gathered based ona first plurality of parameters. The first plurality of data may begathered in real time. The second set of statistical data may include afirst plurality of occupancy data and a second plurality of occupancydata. The first plurality of occupancy data may be associated withenergy consumption behavior of each of a plurality of users presentinside the one or more built environments. The second plurality ofoccupancy data may be associated with an occupancy pattern of each ofthe plurality of users present inside the one or more builtenvironments. The third set of statistical data may include a currentand historical energy storage and supply capacity data associated withthe plurality of energy storage and supply means. The third set ofstatistical data may be accumulated based on a second plurality ofparameters. The third set of statistical data may be accumulated in thereal time. The fourth set of statistical data may include a current andhistorical environmental condition data of at least one of inside andoutside of the one or more built environments. The fourth set ofstatistical data may be received based on a third plurality ofparameters. The fourth set of statistical data may be received in thereal time. The fifth set of statistical data may include current andhistorical recordings of energy pricing state affecting the one or morebuilt environments. The fifth set of statistical data may be gatheredbased on a fourth plurality of parameters. The fifth set of statisticaldata may be gathered in the real time. The comparison may be performedfor segregation of each of the one or more built environments based onsurplus and shortage of energy demand and supply corresponding to thebuilt environment of the one or more built environments. The set ofcontrol strategies may be identified for regulation of the firstplurality of parameters associated with the plurality of energyconsuming devices and the second plurality of parameters associated withthe plurality of energy storage and supply means. The key performanceindicators may be identified corresponding to one or more levels ofcontrol associated with the set of control strategies. The keyperformance indicators may be identified based on operating behavior andstates of each of the plurality of energy consuming devices. Theidentification may be performed in real time. The one or moreinstructional control strategies may be prioritized to achieve the oneor more levels of control. The set of control strategies may include aplurality of operational and non-operational instructions.

BRIEF DESCRIPTION OF THE FIGURES

Having thus described the invention in general terms, reference will nowbe made to the accompanying drawings, which are not necessarily drawn toscale, and wherein:

FIG. 1 illustrates an interactive environment for prioritizinginstructional control strategies affecting operational behavior andstates of a plurality of energy consuming devices and reducingtime-variant energy demand of one or more built environments, inaccordance with various embodiments of the present disclosure;

FIG. 2 illustrates a block diagram for prioritizing instructionalcontrol strategies affecting operational behavior and states of theplurality of energy consuming devices and reducing time-variant energydemand of the one or more built environments, in accordance with variousembodiments of the present disclosure;

FIG. 3 illustrates a block diagram of an energy demand control system,in accordance with various embodiments of the present disclosure;

FIG. 4A and FIG. 4B illustrates a flow chart for prioritizinginstructional control strategies affecting operational behavior andstates of the plurality of energy consuming devices, in accordance withvarious embodiments of the present disclosure; and

FIG. 5 illustrates a block diagram of a communication device, inaccordance with various embodiments of the present disclosure.

It should be noted that the accompanying figures are intended to presentillustrations of exemplary embodiments of the present disclosure. Thesefigures are not intended to limit the scope of the present disclosure.It should also be noted that accompanying figures are not necessarilydrawn to scale.

DETAILED DESCRIPTION

In the following description, for purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present technology. It will be apparent, however,to one skilled in the art that the present technology can be practicedwithout these specific details. In other instances, structures anddevices are shown in block diagram form only in order to avoid obscuringthe present technology.

Reference in this specification to “one embodiment” or “an embodiment”means that a particular feature, structure, or characteristic describedin connection with the embodiment is included in at least one embodimentof the present technology. The appearance of the phrase “in oneembodiment” in various places in the specification are not necessarilyall referring to the same embodiment, nor are separate or alternativeembodiments mutually exclusive of other embodiments. Moreover, variousfeatures are described which may be exhibited by some embodiments andnot by others. Similarly, various requirements are described which maybe requirements for some embodiments but not other embodiments.

Moreover, although the following description contains many specifics forthe purposes of illustration, anyone skilled in the art will appreciatethat many variations and/or alterations to said details are within thescope of the present technology. Similarly, although many of thefeatures of the present technology are described in terms of each other,or in conjunction with each other, one skilled in the art willappreciate that many of these features can be provided independently ofother features. Accordingly, this description of the present technologyis set forth without any loss of generality to, and without imposinglimitations upon, the present technology.

FIG. 1 illustrates an interactive environment for prioritizing one ormore instructional control strategies affecting operational behavior andstates of energy consuming devices associated with one or more builtenvironments, in accordance with various embodiment of the presentdisclosure. The interactive environment facilitates assimilation andanalysis of energy conditions associated with the one or more builtenvironments. The energy conditions include but may not be limited toenergy demand, energy consumption, energy expenses and energy useintensity. The energy conditions are utilized for identification andprioritization of the one or more instructional control strategiesaffecting operational behavior and states of energy consuming devicesinstalled in the one or more built environments. In addition, the energyconditions are utilized for identification and prioritization of the oneor more instructional control strategies to reduce time-variant energydemand of the one or more built environments.

The interactive environment is characterized by the interaction of abuilt environment 102, a plurality of energy consuming devices 104, aplurality of energy storage and supply means 106, a plurality of sensors108 and one or more data collecting devices 110. In addition, theinteractive environment is characterized by the interaction of acommercial power supply grid node 112, one or more renewable energysupply sources 114 and a communication network 116. Furthermore, theinteractive environment is characterized by the interaction of aplurality of environmental sensors 118 and a plurality of energy pricingmodels 120. Moreover, the interactive environment is characterized bythe interaction of an energy demand control system 122, a plurality ofexternal application program interfaces 124 (hereafter “APIs”) and oneor more statistical monitoring devices 126.

In general, the built environment 102 is a closed or semi-closedstructure with one or more number of floors utilized for specificpurposes. Each built environment are utilized to perform a pre-definedoperations and maintenance based on types of services provided by thebuilt environment 102. The types of services include hospitality,travel, work, entertainment, manufacturing and the like. In addition,each type of service provided decides a scale of the operations andmaintenance of the built environment 102. The type of services and themaintenance pertains to the energy consumption associated with each ofthe plurality of energy consuming devices 104. Examples of the builtenvironment 102 include but may not be limited to an office, a mall, anairport, a stadium, a hotel and a manufacturing plant.

The built environment 102 utilizes energy for operations and maintenanceof the built environment 102. The built environment 102 obtains theenergy from a plurality of energy generation and supply sources. Theplurality of energy generation and supply sources include but may not belimited to the commercial power supply grid node 112 and the one or morerenewable energy supply sources 114. The commercial power supply gridnode 112 corresponds to a network of power lines, a plurality oftransformers and one or more equipment employed for the transmission anddistribution of the alternate current power to the built environment102. Further, the one or more renewable energy supply sources 114include but may not be limited to one or more windmills and a pluralitysolar photovoltaic panels.

In an embodiment of the present disclosure, the one or more renewableenergy supply sources 114 are deployed at the built environment 102. Inan example, the plurality of solar photovoltaic panels are installed atthe residential or commercial rooftops. In another embodiment of thepresent disclosure, the one or more renewable energy supply sources 114are deployed at a remote location from the built environment 102. In anexample, the one or more windmills are deployed at countryside farmland.In an embodiment of the present disclosure, the one or more renewableenergy supply sources 114 is directly connected to the plurality ofenergy storage and supply means 106 associated with the builtenvironment 102. The one or more renewable energy supply sources 114directly provides DC energy to the plurality of energy storage andsupply means 106 without going through any voltage or current conversionprocess. In another embodiment of the present disclosure, the one ormore renewable energy supply sources 114 is connected with the builtenvironment 102 to supply available energy through the use of a directcurrent to alternating current inverter.

The plurality of energy storage and supply means 106 is configured tostore the energy and supply to fulfil energy demand associated with thebuilt environment 102. In an embodiment of the present disclosure, theplurality of energy storage and supply means 106 includes one or morebattery cells assembled to create one or more battery packs capable ofcharging and discharging electric energy. In another embodiment of thepresent disclosure, the plurality of energy storage and supply means 106is a high speed flywheel energy storage means. In yet another embodimentof the present disclosure, the plurality of energy storage and supplymeans 106 is pumped hydro energy storage means.

In yet another embodiment of the present disclosure, the plurality ofenergy storage and supply means 106 is non-electrical energy storingmediums. In an example, the energy storage and supply means may becomprised of thermal mass or momentum, such that the calculated amountof energy as converted to heat is stored within the energy storage andsupply means. In addition, the energy is stored and released at acertain rate using heat transfer or pumping as an energy transfermedium. In another example, a building environment, its construction,envelope and contents are utilized as a means to store, transfer andrelease energy passively or actively in a form of heat when combinedwith a means of artificial heating and cooling.

In an embodiment of the present disclosure, the plurality of energystorage and supply means 106 is located at a central location in thebuilt environment 102. The central location associated with the builtenvironment 102 include an electrical room or closet, exterior in aspecialized storage cabinet or container and the like. In anotherembodiment of the present disclosure, the plurality of energy storageand supply means 106 is co-located with each of the plurality of energyconsuming devices 104. In yet another embodiment of the presentdisclosure, the plurality of energy storage and supply means 106 isdistributed throughout the built environment 102. In an example, theplurality of energy storage and supply means 106 is distributed instand-alone forms, plug-in forms and design oriented forms such asfurniture or permanent wall hanging forms or picture frames.

In yet another embodiment of the present disclosure, the plurality ofenergy storage and supply means 106 is built into the building structureor building electrical distribution itself. In yet another embodiment ofthe present disclosure, the plurality of energy storage and supply means106 is in a form of thermal heat mass capture and release usingcalculated capacities of building materials. In yet another embodimentof the present disclosure, the plurality of energy storage and supplymeans 106 is located outside of the built environment 102 in amicro-grid or fractal grid application.

Going further, the built environment 102 is associated with a pluralityof users 128 present inside the built environment 102. The plurality ofusers 128 may be any human operator, human worker, occupants, datamanager, visitors and the like. Each of the plurality of users 128 isassociated with a task. For example, the human operators perform thetask of monitoring and regulating machines. In another example, thehuman workers perform the task of cleaning, sweeping and repairing. Inyet another example, the occupants are the employees that includemanagers, attendants, assistants, clerk, security staff and the like. Inyet another example, the visitors are civilians present for a specificperiod of time.

Each of the plurality of users 128 utilizes a pre-defined amount of theenergy. The pre-defined amount of the energy pertains to a correspondingenergy consuming device of the plurality of energy consuming devices104. Moreover, each of the plurality of energy consuming devices 104performs an operation to meet requirements of the plurality ofoperations associated with the built environment 102. The plurality ofoperations is associated with operation of each of the plurality ofenergy consuming devices 104 installed in the built environment 102. Theplurality of energy consuming devices 104 may be of any type and size.In addition, the plurality of energy consuming devices 104 include aplurality of electrical devices and a plurality of portablecommunication devices.

In an embodiment of the present disclosure, the plurality of energyconsuming devices 104 may have any electrical and mechanicalapplications. Examples of the plurality of energy consuming devices 104include but may not be limited to lighting circuits, refrigerationunits, air conditioning systems, information technology networks, gasboilers, hot water heater, escalators, and elevators. The plurality ofenergy consuming devices 104 consumes a pre-defined amount of the energybased on a power rating, duration of energy usage and the plurality ofoperations performed. The pre-defined amount of the energy consumed bythe plurality of energy consuming devices 104 is based on one or moreenergy physical variables. The one or more energy physical variablesinclude but may not be limited to a power factor, a phase angle, a powerfrequency, a voltage, a current load and a power demand.

The one or more energy physical variables of each of the plurality ofenergy consuming devices 104 is monitored and measured by a plurality ofenergy metering devices. Each of the plurality of energy consumingdevices 104 is combined with the plurality of energy metering devices.In an embodiment of the present disclosure, the plurality of energymetering devices is installed inside each of the plurality of energyconsuming devices 104. The plurality of energy metering devices measureseach of the one or more energy physical variables in real time. Theplurality of energy metering devices include but may not be limited todigital multi-meters, current sensors and wattage meters. In addition,the plurality of energy metering devices facilitates collection of afirst set of statistical data associated with the plurality of energyconsuming devices 104.

The collection of the first set of statistical data uses a method. In anembodiment of the present disclosure, the method involves digitalcollection of the first set of statistical data for each of theplurality of energy consuming devices 104. In another embodiment of thepresent disclosure, the method involves physical collection of the firstset of statistical data for each of the plurality of energy consumingdevices 104. The plurality of energy metering devices monitors a firstplurality of parameters. The first plurality of parameters is associatedwith the plurality of energy consuming devices 104. The first pluralityof parameters includes a set of operational characteristics and a set ofphysical characteristics. The set of operational characteristics includea current rating, a voltage rating, a power rating, a frequency ofoperation, an operating temperature and a device temperature. Inaddition, the set of operational characteristics include a duration ofthe energy usage by each of the plurality of energy consuming devices104 in the built environment 102. Moreover, the set of operationalcharacteristics include a seasonal variation in operation and anoff-seasonal variation in operation. Further, the set of physicalcharacteristics include a device size, a device area, a device physicallocation and a portability of device. In an embodiment of the presentdisclosure, the one or more energy metering devices collects the firstset of statistical data. In addition, the first set of statistical dataincludes a current operational state data and a past operational statedata. The current operational state data and the past operational statedata corresponds to current energy consumption data and the historicalenergy consumption data associated with the plurality of energyconsuming devices 104 of the built environment 102.

Going further, the plurality of energy consuming devices 104 isassociated with the plurality of users 128. The plurality of users 128interacts with the plurality of energy consuming devices 104 installedin the built environment 102 to perform specific operations. The dailyusage and the operating characteristics of plurality of energy consumingdevices 104 are derived from an interface associated with each user ofthe plurality of users 128. Each of the plurality of energy consumingdevices 104 consumes a pre-defined amount of energy during theinterface. The pre-defined amount of energy is derived based on anenergy consumption behavior and an occupancy pattern of each of theplurality of users 128. In an example, each user of the plurality ofusers 128 in the built environment 102 may arrive and leave the builtenvironment 102 during certain hours each day. Each user carries one ormore portable communication devices both in and out of the builtenvironment 102.

Further, the energy consumption behavior and the occupancy pattern isrecorded for each of the plurality of users 128 to obtain a second setof statistical data. The energy consumption behavior and occupancypattern is collected and recorded by a plurality of occupancy detectionmeans. The plurality of occupancy detection means collect the energyconsumption behavior and occupancy pattern associated with the pluralityof users 128 in real time. The plurality of occupancy detection meansare installed inside and outside of the built environment 102. Theplurality of occupancy detection means include a plurality of occupancysensing devices. The plurality of occupancy sensing devices includeoccupancy sensors, door state sensors, motion detectors, microphones,radio frequency identification (hereinafter as “RFID”), radio receivedsignal strength indicators (hereinafter as “RSSI”) and digital or radiofrequency signal processors. Furthermore, the plurality of occupancydetection means include the plurality of sensors 108. The plurality ofsensors 108 include carbon-monoxide sensors, carbon-dioxide sensors,heat sensors, pressure sensors, atmospheric pressure sensors,temperature sensors, energy flow sensors, energy fingerprint sensors onmonitored loads physical touch point sensors and the like.

The first set of statistical data and the second set of statistical datais transferred to the one or more data collecting devices 110 associatedwith the built environment 102. The one or more data collecting devices110 collects the first set of statistical data and the second set ofstatistical data. The one or more data collecting devices 110 performdigital collection and manual collection. In an embodiment of thepresent disclosure, each of the one or more data collecting devices 110is a portable device with an inbuilt API. The inbuilt API of each of theone or more data collection devices 110 is associated with a GlobalPositioning system (hereafter “GPS”). Further, the inbuilt API of eachof the one or more data collection devices 110 is associated with acamera and keypad designed for manual data input from the plurality ofusers 128. In another embodiment of the present disclosure, each of theone or more data collecting devices 110 is a cellular modem. In yetanother embodiment of the present disclosure, each of the one or moredata collecting devices 110 is any suitable data gateway device.

The one or more data collecting devices 110 collects a third set ofstatistical data associated with each of the plurality of energy storageand supply means 106. In an embodiment of the present disclosure, theone or more data collecting devices 110 receives the third set ofstatistical data from the plurality of energy monitoring devicesassociated with each of the plurality of energy storage and supply means106. The plurality of energy monitoring devices monitor a secondplurality of parameters associated with the plurality of energy storageand supply means 106. In addition, the plurality of energy monitoringdevices collect and transfer the second plurality of parametersassociated with the plurality of energy storage and supply means 106 tothe one or more data collecting devices 110 in real time. The secondplurality of parameters include but may not be limited to charging anddischarging rates, temperature characteristics, an energy storage andrelease capacity associated with the plurality of energy storage.

The one or more data collecting devices 110 is associated with thecommunication network 116 through an internet connection. The internetconnection is established based on a type of network. In an embodimentof the present disclosure, the type of network is a wireless mobilenetwork. In another embodiment of the present disclosure, the type ofnetwork is a wired network with a finite bandwidth. In yet anotherembodiment of the present disclosure, the type of network is acombination of the wireless and the wired network for the optimumthroughput of data transmission. The communication network 116 includesa set of channels with each channel of the set of channels supporting afinite bandwidth. The finite bandwidth of each channel of the set ofchannels is based on a capacity of the communication network 116. Thecommunication network 116 transmits a pre-defined size of the first setof statistical data, the second set of statistical data and the thirdset of statistical data to the energy demand control system 122. Thepre-defined size corresponding to the first set of statistical data, thesecond set of statistical data and the third set of statistical data ismeasured in terms of at least one of bits, bytes, kilobytes, megabytes,gigabytes, terabytes and petabytes. Accordingly, the energy demandcontrol system 122 receives the pre-defined size of the first set ofstatistical data, the second set of statistical data and the third setof statistical data. In addition, the energy demand control system 122receives another part of the first set of statistical data, the secondset of statistical data and the third set of statistical data from theplurality of external APIs 124 and third party databases.

Continuing with FIG. 1, the energy demand control system 122 receives afourth set of statistical data and a fifth set of statistical data. Theenergy demand control system 122 receives the fourth set of statisticaldata from the plurality of environmental sensors 118 through thecommunication network 116. The plurality of environmental sensors 118detect and collect environmental and weather conditions associated withthe built environment 102 in real time. In addition, the plurality ofenvironmental sensors 118 transfer the environmental and weatherconditions to the energy demand control system 122 in real time. In anembodiment of the present disclosure, the plurality of environmentalsensors 118 is present inside the built environment 102. In anotherembodiment of the present disclosure, the plurality of environmentalsensors 118 is present outside the built environment 102. Further, theenergy demand control system 122 receives the fifth set of statisticaldata from the plurality of energy pricing models 120. The plurality ofenergy pricing models 120 is configured to record energy pricesassociated with the built environment 102.

The energy demand control system 122 receives another part of the fourthset of statistical data and the fifth set of statistical data from theplurality of external APIs 124 and third party databases. The pluralityof external APIs 124 and the third party databases are configured tocollect, store and transmit weather history and weather forecasts. Inaddition, the plurality of external APIs 124 and the third partydatabases are configured to collect, store and transmit billing data, apast energy consumption data and metered energy data. Furthermore, theplurality of external APIs 124 and the third party databases areconfigured to collect, store and transmit financial or non-financialbusiness data. The financial or non-financial business data comes frombusiness management software. Example of the business managementsoftware includes Enterprise Resources Planning (ERP) software.

The energy demand control system 122 analyzes the first set ofstatistical data, the second set of statistical data, the third set ofstatistical data, the fourth set of statistical data and the fifth setof statistical data. The analysis is done by performing one or morestatistical functions (discussed below in detailed description of FIG.2). The energy demand control system 122 performs the one or morestatistical functions to generate a plurality of statistical results.The plurality of statistical results pertains to the energy consumption(discussed below in detailed description of FIG. 2). The plurality ofstatistical results obtained from the analysis is used as a referencebasis of the energy consumption to identify and prioritize the one ormore instructional control strategies affecting the operational behaviorand states of the plurality of energy consuming devices 104.

Further, the energy demand control system 122 parses the first set ofstatistical data, the second set of statistical data, the third set ofstatistical data, the fourth set of statistical data and the fifth setof statistical data. The energy demand control system 122 performparsing by developing an energy usage profile (discussed below indetailed description of FIG. 2). In addition, the energy demand controlsystem 122 compares the energy usage profile. The energy demand controlsystem 122 compares the energy usage profile to segregate the builtenvironment 102 based on surplus and shortage of energy demand andsupply (described below in detailed description of FIG. 2).

Going further, the energy demand control system 122 identify a set ofcontrol strategies. The set of control strategies includes a pluralityof operational and non-operational instructions (mentioned below indetailed description of FIG. 2). The energy demand control system 122identifies the set of control strategies for regulating the firstplurality of parameters associated with the plurality of energyconsuming devices 104. In addition, the energy demand control system 122identifies the set of control strategies for regulating the secondplurality of parameters associated with the plurality of energy storageand supply means 106. Moreover, the energy demand control system 122identifies key performance indicators corresponding to one or morelevels of control associated with the set of control strategies(discussed below in detailed description of FIG. 2). Further, the energydemand control system 122 prioritize the one or more instructionalcontrol strategies from the set of control strategies. The energy demandcontrol system 122 prioritize the one or more instructional strategiesbased on the comparison of the energy usage profile (explained below indetailed description of FIG. 2).

Further, the energy demand control system 122 transfers the plurality ofstatistical results along with the one or more instructional controlstrategies to the one or more statistical monitoring devices 126. Theone or more statistical monitoring devices 126 is configured to receiveand display at least one of the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical data. Inaddition, the one or more statistical monitoring devices 126 areconfigured to receive and display at least one of the key performanceindicators, the plurality of statistical results and the one or moreinstructional control strategies for proper monitoring and regulation.The one or more statistical monitoring devices 126 is a device capableof receiving the first set of statistical data, the second set ofstatistical data, the third set of statistical data, the fourth set ofstatistical data and the fifth set of statistical data from the energydemand control system 122. Also, the one or more statistical monitoringdevices 126 is a device capable of receiving the key performanceindicators, the plurality of statistical results and the one or moreinstructional control strategies from the energy demand control system122.

It may be noted that in FIG. 1, the energy demand control system 122transfers the first set of statistical data, the second set ofstatistical data, the third set of statistical data, the fourth set ofstatistical data, the fifth set of statistical data, the plurality ofstatistical results and the one or more instructional control strategiesto the one or more statistical monitoring devices 126; however, thoseskilled in the art would appreciate that the energy demand controlsystem 122 transfers the first set of statistical data, the second setof statistical data, the third set of statistical data, the fourth setof statistical data and the fifth set of statistical data, the pluralityof statistical results and the one or more instructional controlstrategies to more number of statistical monitoring devices.Furthermore, it may be noted that in FIG. 1, the built environment 102is connected to the energy demand control system 122 through thecommunication network 116; however, those skilled in the art wouldappreciate that more number of built environments are connected to theenergy demand control system 122 through the communication network 116.

FIG. 2 illustrates a block diagram 200 for prioritizing the one or moreinstructional control strategies of the built environment 102, inaccordance with various embodiments of the present disclosure. The oneor more instructional control strategies affects the operationalbehavior and states of the plurality of energy consuming devices 104associated with the built environment 102. Moreover, the one or moreinstructional control strategies are prioritized to reduce time-variantenergy demand of the built environment 102. It may be noted that toexplain the system elements of FIG. 2, references will be made to thesystem elements of the FIG. 1.

The block diagram 200 includes the built environment 102, commercialpower supply grid node 112, the one or more renewable energy supplysources 114, the energy demand control system 122 and the plurality ofexternal APIs 124 (as discussed above in detailed description of FIG.1). In addition, the block diagram 200 includes the plurality ofenvironmental sensors 118 and the plurality of energy pricing models 120and the one or more statistical monitoring devices 126 (as discussedabove in detailed description of FIG. 1). Moreover, the block diagram200 includes a network based automatic control system 202 and thirdparty databases 206. Furthermore, the energy demand control system 122includes a server 204. In addition, the server 204 includes a database204 a and a processor 204 b.

Each of the plurality of energy consuming devices 104 is associated withone or more energy physical variables (as described above in detaileddescription of FIG. 1). The one or more energy physical variablesdefines the energy consumption in the real time based on the load. In anembodiment of the present disclosure, each of the plurality of energyconsuming devices 104 is associated with the plurality of energymetering devices. The plurality of energy metering devices digitallymeasures one or more energy physical variables in the real time toobtain the first set of statistical data (as discussed above in detaileddescription of FIG. 1). The plurality of energy metering devicesincludes one or more digital meters, one or more digital current andvoltage sensors, the multi-meters, watt-meters, supervisory control anddata acquisition (SCADA) and the like.

The energy demand control system 122 collects the first set ofstatistical data associated with the plurality of energy consumingdevices 104 from the plurality of energy metering devices. The first setof statistical data includes the current operational state dataassociated with the plurality of energy consuming devices 104 and a pastoperational state data associated with the plurality of energy consumingdevices 104. The operational state data is associated with thepre-defined amount of energy consume by each of the plurality of energyconsuming devices 104 in real time. The plurality of energy consumingdevices 104 consume the pre-defined amount of energy to perform aspecific operation (as discussed above in detailed description of FIG.1).

Further, the energy demand control system 122 fetches the second set ofstatistical data associated with an occupancy behavior of the pluralityof users 128 present inside each of the built environment 102. Theenergy demand control system 122 fetches the second set of statisticaldata from the plurality of occupancy detection means. The second set ofstatistical data includes a first plurality of occupancy data and asecond plurality of occupancy data. The first plurality of occupancydata is associated with energy consumption behavior of each of theplurality of users 128 present inside the built environment 102. Thesecond plurality of occupancy data is associated with the occupancypattern of each of the plurality of users 128 present inside the builtenvironment 102.

The first plurality of occupancy data is associated with interactionbetween the plurality of energy consuming devices 104 and the pluralityof users 128. In an example, a person X check-in to a hotel A. Theperson X uses the elevator to go upstairs, unlock the room by digitalcard swap and turns on the lighting and air conditioning unit. Theinteraction of the person X with the elevator, the digital card swapsdoor, the lightings and the air conditioning unit results in thepre-defined load consumption. The plurality of users 128 consumes thepre-defined amount of energy associated with the built environment 102.

The second plurality of occupancy data is associated with the occupancypattern of the plurality of users 128. The occupancy pattern of theplurality of users 128 varies with time, location, weather, season andthe like. The occupancy pattern of the plurality of users 128 varieswith different zones of the built environment 102. In an example, theoccupancy pattern of the plurality of users 128 in shopping mallsincreases during the festive seasons. In another example, the occupancypattern at the rugby ground increases during the match day.

The energy consumption behavior and occupancy pattern is recorded andcounted by the plurality of occupancy detection means to obtain thesecond set of statistical data (as described above in detaileddescription of FIG. 1). In addition, the plurality of occupancydetection means record and count based on the one or morespecifications. The one or more specifications include heat signature,identification cards, Bluetooth and the like. In an example, the recordof first time visitors and frequent visitors is maintained for fastercollection of the second set of statistical data. Further, the energyusage pattern of each of the plurality of users 128 creates a unique andaggregated consumption of the energy. The unique and aggregatedconsumption of the energy is based on a variation in number of theplurality of users 128. The variation in the number of the plurality ofusers 128 is based on days, months, seasons, events and time of year. Inaddition, the variation in the number of the plurality of users 128 maybe based on architectural configurations of the built environment 102.In an example, the occupancy pattern of the plurality of users 128 inshopping malls increases during the festive seasons. In another example,the occupancy pattern at the soccer ground increases during the matchday.

Further, the energy demand control system 122 accumulates the third setof statistical data associated with each of the plurality of energystorage and supply means 106 from the plurality of energy monitoringdevices. The third set of statistical data includes a current andhistorical energy storage and supply capacity data associated with theplurality of energy storage and supply means 106. The plurality ofenergy monitoring devices record and collect energy storage and supplycapacity data associated with the plurality of energy storage and supplymeans 106 to obtain the third set of statistical data. The energy demandcontrol system 122 accumulates the third set of statistical data basedon the second plurality of parameters (as mentioned above in detaileddescription of FIG. 1).

The energy demand control system 122 receives the fourth set ofstatistical data from the plurality of environmental sensors 118associated with the built environment 102 (discussed above in detaileddescription of FIG. 1). In addition, the energy demand control system122 receives the fourth set of statistical data from the plurality ofexternal APIs 124 and the third party databases 206. The fourth set ofstatistical data includes the current and historical environmentalcondition data of at least one of inside and outside of the builtenvironment 102. The fourth set of statistical data is received by theenergy demand control system 122 based on a third plurality ofparameters. In an embodiment of the present disclosure, the thirdplurality of parameters include but may not be limited to a means ofrecording environmental data having temperature, humidity and airpressure associated with each of the plurality of environmental sensors.

Further, the energy demand control system 122 gathers the fifth set ofstatistical data from the plurality of energy pricing models 120. Thefifth set of statistical data includes current and historical recordingsof energy pricing state affecting the built environment 102. Theplurality of energy pricing models 120 record and transfer the energypricing to the energy demand control system 122 in real time through thecommunication network 116. In addition, the energy demand control system122 gathers the fifth set of statistical data from the plurality ofexternal APIs 124 and the third party databases 206 (as discussed abovein detailed description of FIG. 1). The fifth set of statistical data isgathered based on a fourth plurality of parameters. In an embodiment ofthe present disclosure, the fourth plurality of parameters include ameans of recording energy pricing data having an energy pricing model,an energy price signal associated with the built environment 102.

Going further, the energy demand control system 122 performs theanalysis of the first set of statistical data, the second set ofstatistical data, the third set of statistical data, the fourth set ofstatistical data and the fifth set of statistical data. The energydemand control system 122 performs the one or more statistical functionsto generate the plurality of statistical results. The one or morestatistical functions include deriving energy demand values associatedwith the real time energy consumption. The energy demand control system122 derives the energy demand values by translating the currentoperational state data and the past operational state data associatedwith the plurality of energy consuming devices 104. The energy demandcontrol system 122 derives the energy demand values for a pre-definedinterval of time.

Further, the one or more statistical functions include imputing one ormore data entries in the first set of statistical data, the second setof statistical data and the third set of statistical data. The imputingof the one or more data entries is performed to minimize errors inderiving the energy consumption and demand associated with the builtenvironment 102 for a given time interval. Moreover, the energy demandcontrol system 122 imputes the one or more data entries by using anapplication of at least one of the statistical regression, interpolationand extrapolation.

The one or more statistical functions include correlating the currentoperational state data with the past operational state data. The energydemand control system 122 correlates the current operational state datawith the past operational state data associated with the each of theplurality of energy consuming devices 104. The current operational statedata and the past operational state data are correlated to determine thepotential for improvement in energy consumption of each of the pluralityof energy consuming devices 104. In addition, the energy demand controlsystem 122 correlate a current energy storage capacity and a past energystorage capacity associated with each of the plurality of energy storageand supply means 106. The current energy storage capacity and the pastenergy storage capacity are correlated to determine the potential forimprovement in charge/discharge cycles and energy storage capacity ofeach of the plurality of energy storage and supply means 106.

Accordingly, the analysis of the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical dataprovides the plurality of statistical results. The plurality ofstatistical results pertains to the energy consumption. In addition, theplurality of statistical results is based on a statistical data model.The statistical data model provides a complete insight into the energyconsumption trend. The plurality of statistical results includes one ormore graphs, one or more charts, one or more tables and one or morestatistical maps of energy consumption. The plurality of statisticalresults are obtained as a function of duration of the operations of theplurality of energy consuming devices 104 and energy storage and supplycapacity of the plurality of energy storage and supply means 106. Inaddition, the plurality of statistical results are obtained as afunction of environmental conditions, and energy pricing affecting thebuilt environment 102.

In an example, the plurality of statistical results include a table andchart of monthly energy consumption of the built environment 102 and atable of a total monthly variable energy load. In another example, theplurality of statistical results includes a pie chart to show aseparation of the energy use in the built environment 102 and a table ofenergy consumption per month and air conditioner loads. In yet anotherexample, the plurality of statistical results includes a statisticalchart depicting a kWh consumption based on load type, a bar graph ofexpected air conditioner savings and service costs. In yet anotherexample, the plurality of statistical results include a bar chart ofgross rental, service and licensing costs of at least one of airconditioning units, air conditioning control means, statistical softwareand networks. In yet another example, the plurality of statisticalresults includes the statistical chart of total kWh consumed per room asa function of cold degree days.

The energy demand control system 122 parses the first set of statisticaldata, the second set of statistical data and the third set ofstatistical data. The energy demand control system 122 develops anenergy usage profile. The energy demand control system 122 develops theenergy usage profile of each category of the plurality of energyconsuming devices 104, each of the plurality of energy storage andsupply means 106 and each of the plurality of users 128. In addition,the energy demand control system 122 develops the energy usage profileassociated with each zone of the floor, each group of zones of floor,each floor of the built environment and each of the one or more builtenvironments.

The energy demand control system 122 compares the energy usage profileassociated with each of the plurality of energy consuming devices 104.In addition, the energy demand control system 122 compares the energyusage profile associated with each user of the plurality of users 128.Moreover, the energy demand control system 122 compares the energy usageprofile of each floor of a built environment. Also, the energy demandcontrol system 122 compares the energy demand profile of each of the oneor more built environments. The energy demand control system 122compares the energy usage profile for segregating each of the one ormore built environments based on surplus and shortage of energy demandand supply.

The energy demand control system 122 identifies the set of controlstrategies for regulating the first plurality of parameters associatedwith the plurality of energy consuming devices 104. In addition, theenergy demand control system 122 identifies the set of controlstrategies for regulating the second plurality of parameters associatedwith the plurality of energy storage and supply means 106. The one ormore instructional control strategies includes a potential operationaland non-operational instructions for optimizing the operating state ofthe plurality of energy consuming devices 104. In addition, the one ormore instructional control strategies includes the potential operationaland non-operational instructions for improving the energy storagecapacity of the plurality of energy storage and supply means 106.

The potential operational and non-operational instructions includeregulating power supply of each of the plurality of energy consumingdevices 104 based on the occupancy pattern, energy demand andarchitectural design of the built environment 102. In addition, thepotential operational and non-operational instructions includeregulating energy consumption duration of the plurality of energyconsuming devices 104. Moreover, the potential operational andnon-operational instructions include notifying a list of malfunctioningdevices of the plurality of energy consuming devices 104. Furthermore,the potential operational and non-operational instructions includeperforming one or more operations on the plurality of energy consumingdevices 104. The one or more operations are selected from a group ofoperations consisting of upgrading, downgrading, replacing and repairingof the plurality of energy consuming devices 104.

Further, the operational and non-operational instructions includeprompting the plurality of energy storage and supply means 106 to startand stop charge cycles at specific time periods for reducing energyconsumption costs. In addition, the operational and non-operationalinstructions include prompting the plurality of energy storage andsupply means 106 to start and stop discharge cycles for controlling thepeak loading periods. Moreover, the operational and non-operationalinstructions include regulating the charging and dischargingcharacteristics of each of the plurality of energy storage and supplymeans 106.

The energy demand control system 122 identifies the key performanceindicators for each of the plurality of energy consuming devices 104.The energy demand control system 122 identifies the key performanceindicators based on the operating behavior and state of each of theplurality of energy consuming devices 104. In addition, the energydemand control system 122 identifies the key performance indicators foreach zone of the built environment 102. The key performance indicatorsfor each zone of the built environment is identified based on the energyusage profile associated with the corresponding zone of the builtenvironment 102. In an example of a hotel, multiple air conditioningcompressors may be turning on and off to transfer energy and maintain aspecific temperature within an enclosed environment of the hotel.Multiplied by 100 times, these air conditioners may coincidentallyoscillate on and off at the same time. The plurality of energy meteringdevices is regularly reading the state of the air conditioningcompressor as a value, on or off or zero to one hundred and transmittingthis back to the energy demand control system 122. The wave form andfrequency of each compressor is recorded and after a short period oftime can be assimilated to identify a key performance indicator.

Further, the key performance indicators are identified corresponding tothe one or more levels of control associated with the set of controlstrategies. The one or more control levels are achieved by executing theone or more instructional control strategies in a pre-defined sequenceto reduce the time-variant energy demand of the built environment 102.The energy demand control system 122 executes the one or moreinstructional control strategies in the pre-defined sequence byprioritizing the one or more instructional control strategies. Theenergy demand control system 122 prioritize the one or moreinstructional control strategies to achieve the one or more controllevels for reducing time variant energy demand.

In an embodiment of the present disclosure, a first control level isperformed by analyzing the real time operating behavior and state of theplurality of energy consuming devices 104 and regulating the operatingstates of each of the plurality of energy consuming devices 104 in timeseries. The operating states of each of the plurality of energyconsuming devices 104 is regulated so that the minimum possible numberof load states gets overlapped at the same given moment in time. In anexample of a hotel building, multiple air conditioning compressors maybe turning on and off to transfer energy and maintain a specifictemperature within an enclosed environment. Multiplied by 100 times,these air conditioners may coincidentally oscillate on and off at thesame time. The plurality of energy metering devices regularly collectsthe state of the air conditioning compressor as a value, on or off orzero to one hundred and transmitting this back to the network gateway.The energy consumption and frequency of usage of each compressor isrecorded and after a short period of time can be assimilated to identifya key performance indicator. At a specific moment of time, the highestdemand unit is operating at a frequency of 6 cycles per hour (the“frequency”) or 3 minutes (the “amplitude”) each 7 minutes and thelowest demand unit is operating 3 cycles per hour or 3 minutes each 17minutes. The energy demand control system 122 executes the first controllevel by moving each of the 100 air conditioning unit cycles forwards orbackwards in time so that the fewest number are summed at a given momentin time. The energy demand control system 122 reorders and prioritizesthe operational sequence by sending a control signal to each of the 100air conditioning compressors to regulate the operating states in realtime.

In an embodiment of the present disclosure, a second control level isperformed based on the comparison of the key performance indicatorsassociated with the plurality of energy consuming devices 104. Theenergy demand control system 122 prioritize the instructional controlstrategies for each of the plurality of energy consuming devices 104based on the key performance indicators. In addition, the energy demandcontrol system 122 prioritize each of the plurality of energy consumingdevices 104 based on real time operating states to minimize total energyload at a specific period of time. In an example, a certain airconditioning compressor installed in room X may need to operatesubstantially more than others within an artificially cooled buildingdue to the orientation and heat load from the sun. The energy demandcontrol system 122 analyzes the current operating state, identify andcompare the key performance indicator of the air conditioning compressorof room X with other air conditioning units. In addition, the energydemand control system 122 prioritize the air conditioning compressorinstalled in the room X over other air conditioning compressor unitsinstalled in the building. In addition, the energy demand control system122 prioritize the control instructions regulating the operationalcharacteristics of the air conditioning compressor installed in room X.

In an embodiment of the present disclosure, a third control level isperformed by considering the second set of statistical data associatedwith the plurality of users 128 and the fourth set of statistical dataassociated with the environmental conditions. The energy demand controlsystem 122 prioritize the one or more instructional control strategiesbased on the environmental conditions and occupancy. Moreover, theenergy demand control system 122 prioritize the instructional controlstrategies for each zone of the built environment 102. For example, in ahotel with many rooms and many air conditioning compressors, the energydemand control system 122 receives both the current operating state ofthe compressor for each room as well as the current temperature andoccupancy. The energy demand control system 122 prioritize the controlstrategies for each room first by waveform characteristics (frequencyand amplitude), then by current temperature for each room and finally byoccupancy. The energy demand control system 122 provides a high level ofmanipulation priority to the rooms with unoccupied state. The energydemand control system 122 prioritize the instructional controlstrategies for the unoccupied rooms such that the frequency andamplitude of those unoccupied rooms gets lowered.

In an embodiment of the present disclosure, a fourth control level willimprove an actual efficiency of each of the plurality of energyconsuming devices 104 by optimizing the total energy consumption at agiven moment in time. The actual efficiency is improved by regulatingthe operating states of each of the plurality of energy consumingdevices 104 in real time. The energy demand control system 122prioritizes the instructional control strategies to decrease thefrequency of usage and increase the amplitude of the plurality of energyconsuming devices 104. For example, the energy demand control system 122regulates the operating state of compressor with a 6 cycle per hourfrequency and a three-minute amplitude to 3 cycles per hour frequencyand a six-minute amplitude. This increases the efficiency of thecompressor units by reducing the number of cycle starts. In addition, anaverage energy consumption of 200 Watts per compressor per hourcorresponding to the 6 cycles per hour frequency and three-minuteamplitude is reduced to 180 Watts per compressor per hour correspondingto the 3 cycles per hour frequency and six-minute amplitude. The energydemand control system 122 continues to incrementally decrease the numberof cycles to achieve the optimum energy consumption. For example, if thecycle frequency was further reduced to two, 9 minute cycles and theenergy consumption increases from 180 Watts per compressor per hour to190 Watts per hour, the energy demand control system 122 frequency oramplitude would be reverted back towards an optimal value of three, 6minutes cycles.

In an embodiment of the present disclosure, a fifth control level isperformed by time-variant shifting of usage of each of the plurality ofenergy consuming devices 104 associated with the built environment 102.The time-variant shifting and scheduling is performed for regulating theenergy usage profile and rendering steeper energy demand curves for thebuild environment 102. The energy demand control system 122 analyzes andidentifies a threshold level associated with the energy demandconcentrated over a limited period of time. The energy demand controlsystem 122 prompts the plurality of energy storage and supply means 106to discharge for optimally reducing a peak level of energy demand basedon validation of an increase in the energy demand above a thresholdlevel. For example, the energy demand control system 122 reduces theenergy demand by application of the first control level, the secondcontrol level, the third control level and the fourth control level. Theenergy demand control system 122 prioritize the one or moreinstructional control strategies to reduce the maximum concurrent demandfrom 100 air conditioning unit to 20 air conditioning units. The maximumconcurrent demand is reduced while maintaining a consistent averageindoor temperature range in accordance with the comfort design anddemand of the buildings occupants. Out of the 20 concurrently operatingair conditioning units it will be possible to either instantaneously orin a rapid staged succession turn off all the AC units such that nonewere operating. The temperature would begin to rise quite dramaticallywithin the building in which no air conditioning units were operating atall. This creates a steep and hollow demand trough within the buildingenergy usage profile. It would then be possible to start turning on ACunits in rapid succession in order to initiate a new cooling load.Instead of prompting the 20 air conditioning units to turn on, theenergy demand control system 122 prompts the 40 air conditioning unitsallowing faster recovery of the now higher indoor temperature down to alower temperature. Further, the energy demand control system 122 promptsthe plurality of energy storage and supply means 106 to discharge andsupply the energy to the additional 20 air conditioning units. Theenergy consumption identical to the condition of only 20 airconditioning units operating for a given time interval is maintained asthe additional 20 air conditioning units utilizes the energy dischargedfrom the plurality of energy storage and supply means 106. This wouldprovide an effective energy demand reduction provided by the pluralityof energy storage and supply means 106 equivalent to the demandgenerated by 20 air conditioning units. The energy demand control system122 prompts the plurality of energy storage and supply means 106 to stopdischarging and supplying the energy as soon as average temperaturerequirement is restored in the built environment 102. This results insteep and short discharge intervals of the plurality of energy storageand supply means 106.

In an embodiment of the present disclosure, a sixth control level isperformed by manipulating the operating state of the plurality of energyconsuming devices 104 and the plurality of energy storage and supplymeans 106. The energy demand control system 122 prioritize the one ormore instructional control strategies to operate the plurality of energyconsuming devices 104. The plurality of energy consuming devices 104operates in intervals based on a specific waveform requirement allowingample time to charge and discharge the plurality of energy storage andsupply means 106 while maintaining a constant load target requirementand optimal environmental conditions. In an example, 20 air conditioningunits is controlled for a given specific indoor temperature requirement,based on given outdoor weather conditions. The energy demand controlsystem 122 alternate the operation of 10 air conditioning units insequence with the charge and discharge cycles of the plurality of energystorage and supply means 106. This reduces the sinusoidal net averagedemand, while maintaining the average indoor temperature. The energydemand control system 122 prompts the 10 air conditioning units to turnoff, leaving 10 air conditioning units operating at a specific timeinterval. In addition, the energy demand control system 122 prompts theplurality of energy storage and supply means 106 to start charging at arate equivalent to the power consumption of 10 AC units such that thetotal net demand remains equivalent to 20 air conditioning units.

In an embodiment of the present disclosure, a seventh control level isperformed by integrating the plurality of energy storage and supplymeans 106 to a micro-grid, campus or power grid control, management orsoftware platform. The seventh control level is performed to optimizeand reduce the time variant energy demand across the one or more builtenvironments. The energy demand control system 122 compares the energydemand and consumption associated with each built environment of the oneor more built environments. In an example, out of 5 buildings within themicro-grid, the energy demand control system 122 identifies threebuildings each have a very similar energy demand profile on Wednesdaysbetween 10:00 am and 3:00 pm. Further, the energy demand control system122 analyzes and optimizes the time variant energy demand of each 5buildings and found that a different set of 2 buildings have acoincidental demand requirement between 2:00 pm and 6:00 pm. The energydemand requirement of the 2 buildings overlaps the first three buildingsby 1 hour during 2:00 pm to 3:00 pm in the afternoon.

The energy demand control system 122 shifts the second building setdemand by a period of one hour later such that the total average demandacross the buildings between the hours of 10:00 am and 6:00 pm remainsthe same. This results in reduction of maximum energy consumption whichnormally occurs at 2 pm.

The energy demand control system 122 prioritize and executes the one ormore instructional control strategies through the communication network116. In an embodiment, the energy demand control system 122 executes theone or more instructional control strategies through the network basedautomatic control system 202. The network based automatic control system202 is associated with the built environment 102. In addition, thenetwork based automatic control system 202 is associated with aplurality of electrical control relays. In addition, the network basedautomatic control system 202 is associated with a microprocessor basedswitches. The network based automatic control system 202 sends one ormore control signals based on the one or more instructional controlstrategies. The network based automatic control system 202 automaticallyexecutes the one or more instructional control strategies to the builtenvironment 102. The network based automatic control system 202 controlsthe operation of each of the plurality of energy consuming devices 104.In addition, the network based automatic control system 202 controls theplurality of energy consuming devices 104 based on the occupancybehavior of the plurality of users 128 and energy storage capacity ofthe plurality of energy storage and supply means 106. Moreover, thenetwork based automatic control system 202 controls the plurality ofenergy consuming devices 104 based on weather conditions and real timeenergy pricing associated with the built environment 102. Furthermore,the network based automatic control system 202 controls the plurality ofenergy storage and supply means 106 based on the real time energydemand, weather conditions and forecasts, and real time energy pricingassociated with the built environment 102.

Further, the energy demand control system 122 provides the improvementin the prioritization of the one or more instructional controlstrategies. The improvement in the prioritization is obtained from alearning algorithm. The learning algorithm accelerates assessment andthe analysis of one or more data points. The one or more data pointsassociate with the energy consumption of each of the plurality of energyconsuming devices 104 and each of the plurality of energy storage andsupply means 106. The energy demand control system 122 utilizes the oneor more data points to create a continuous closed control and feedbackloop for optimizing the operating state of the plurality of energyconsuming devices 104. In addition, the energy demand control system 122utilizes the one or more data points to create a continuous closedcontrol and feedback loop for improving the energy storage capacity ofthe plurality of energy storage and supply means 106.

Further, the energy demand control system 122 stores the first set ofstatistical data, the second set of statistical data, the third set ofstatistical data, the fourth set of statistical data and the fifth setof statistical data in the database 204 a. In addition, the energydemand control system 122 stores the key performance indicators, theplurality of statistical results and a log file having one or moreinstructional control strategies in the database 204 a. Moreover, theenergy demand control system 122 stores the first set of statisticaldata, the second set of statistical data, the third set of statisticaldata, the fourth set of statistical data and the fifth set ofstatistical data in real time. In addition, the energy demand controlsystem 122 stores the key performance indicators, the plurality ofstatistical results and the log file having one or more instructionalcontrol strategies in real time.

The energy demand control system 122 updates the first set ofstatistical data, the second set of statistical data, the third set ofstatistical data, the fourth set of statistical data and the fifth setof statistical data. In addition, the energy demand control system 122updates the key performance indicators, the plurality of statisticalresults and the log file having one or more instructional controlstrategies. Moreover, the energy demand control system 122 updates thefirst set of statistical data, the second set of statistical data, thethird set of statistical data, the fourth set of statistical data andthe fifth set of statistical data in real time. In addition, the energydemand control system 122 updates the key performance indicators, theplurality of statistical results and the log file having one or moreinstructional control strategies in real time.

The energy demand control system 122 displays the first set ofstatistical data, the second set of statistical data, the third set ofstatistical data, the fourth set of statistical data and the fifth setof statistical data on the one or more statistical monitoring devices126 in real time. In addition, the energy demand control system 122displays the key performance indicators, the plurality of statisticalresults and the log file having one or more instructional controlstrategies on the one or more statistical monitoring devices 126 in realtime.

FIG. 3 illustrates a block diagram 300 of the energy demand controlsystem 122, in accordance with various embodiment of the presentdisclosure. It may be noted that to explain the system elements of FIG.3, references will be made to the system elements of the FIG. 1 and theFIG. 2. The energy demand control system 122 includes a collectionmodule 302, a fetching module 304, an accumulation module 306, areception module 308, a gathering module 310 and a parsing module 312.In addition, the energy demand control system 122 includes an analyzingmodule 314, a comparison module 316, an identification module 318 and aprioritizing module 320. Moreover, the energy demand control system 122includes a storage module 322, an updating module 324 and a displayingmodule 326. The above mentioned modules are configured for prioritizingthe one or more instructional control strategies affecting theoperational behavior and states of the plurality of energy consumingdevices 104 and reducing the time-variant energy demand of the builtenvironment 102.

The collection module 302 collects the first set of statistical dataassociated with each of the plurality of energy consuming devices 104installed in the built environment 102. The first set of statisticaldata includes the current operational state data and the pastoperational state data associated with the plurality of energy consumingdevices 104. The plurality of energy metering devices collects the firstset of statistical data. The plurality of energy metering devicestransfer the first set of statistical data to the one or more datacollecting devices 110. The one or more data collecting devices 110transfer the first set of statistical data to the energy demand controlsystem 122 (as explained above in the detailed description of FIG. 1 andFIG. 2).

The fetching module 304 fetches the second set of statistical dataassociated with the occupancy behavior of the plurality of users 128present inside the built environment 102. The second set of statisticaldata includes the first plurality of occupancy data and the secondplurality of occupancy data. The first plurality of occupancy dataassociated with the energy consumption behavior of each of the pluralityof users 128 present inside the built environment 102. In addition, thesecond plurality of occupancy data is associated with the occupancypattern of each of the plurality of users 128 present inside the builtenvironment 102. The plurality of occupancy detection means and theplurality of sensors 108 fetches the second set of statistical data inreal time. In addition, the plurality of occupancy detection means andthe plurality of sensors 108 transfer the second set of statistical datato the energy demand control system 122 (as discussed above in detaileddescription of FIG. 1 and FIG. 2).

The accumulation module 306 accumulates the third set of statisticaldata associated with each of the plurality of energy storage and supplymeans 106 associated with the built environment 102. The third set ofstatistical data includes the current and historical energy storage andsupply capacity data associated with the plurality of energy storage andsupply means 106. The plurality of energy monitoring devices accumulatesthe energy storage and supply capacity data associated with each of theplurality of energy storage and supply means 106 in real time to obtainthe third set of statistical data. In addition, the plurality of energymonitoring devices transfer the third set of statistical data to theenergy demand control system 122 (as explained above in detaileddescription of FIG. 1 and FIG. 2).

The reception module 308 receives the fourth set of statistical dataassociated with each of the plurality of environmental sensors 118. Thefourth set of statistical data includes the current and historicalenvironmental condition data of at least one of inside and outside ofthe built environment 102. The plurality of environmental sensors 118records the environmental condition data in real time to obtain thefourth set of statistical data. In addition, the plurality ofenvironmental sensors 118 transfers the fourth set of statistical datato the energy demand control system 122. Moreover, the reception module308 receives the fourth set of statistical data from the plurality ofexternal APIs 124 and the third party databases 206 (as discussed abovein detailed description of FIG. 1 and FIG. 2).

The gathering module 310 gathers the fifth set of statistical dataassociated with each of the plurality of energy pricing models 120. Thefifth set of statistical data includes the current and historicalrecordings of the energy pricing state affecting the built environment102. The plurality of energy pricing models 120 record the real timeenergy pricing state associated with the built environment 102 to obtainthe fifth set of statistical data. In addition, the plurality of energypricing models transfer the fifth set of statistical data to the energydemand control system 122. Moreover, the gathering module 310 gathersthe fifth set of statistical data from the plurality of external APIs124 and the third party databases 206 (as explained above in detaileddescription of FIG. 1 and FIG. 2).

Further, the parsing module 312 parses the first set of statisticaldata, the second set of statistical data, the third set of statisticaldata, the fourth set of statistical data and the fifth set ofstatistical data. The parsing module 312 parses the first set ofstatistical data, the second set of statistical data and the third setof statistical data based on the physical location of each of theplurality of energy consuming devices 104. In addition, the parsingmodule 312 parses the first set of statistical data, the second set ofstatistical data and the third set of statistical data based on theoccupancy pattern of the plurality of users 128. Moreover, the parsingmodule 312 parses the first set of statistical data, the second set ofstatistical data and the third set of statistical data based on theweather conditions and real time energy pricing state. Furthermore, theparsing module 312 performs parsing by developing the energy usageprofile of each category of energy consuming devices 104 and each userof the plurality of users 128. In addition, the parsing module 312performs parsing by developing energy usage profile of each floor of thebuilt environment 102 and each of the one or more built environments (asexplained above in the detailed description of FIG. 1 and FIG. 2).

The analyzing module 314 analyzes the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical data.The analyzing module 314 includes a deriving module 314 a, an imputingmodule 314 b and a correlating module 314 c. The deriving module 314 aderives the energy demand values associated with the energy consumptionof the built environment 102. The deriving module 314 a derives theenergy demand values by translating the current operational state dataand the past operational state data associated with the plurality ofenergy consuming devices 104 into the energy demand values. In addition,the deriving module 314 a derives the energy demand values from thecurrent operational state data and the past operational state data forthe pre-defined interval of time (as discussed in detailed descriptionof FIG. 1 and FIG. 2).

Further, the imputing module 314 b imputes the one or more data entriesin the first set of statistical data, the second set of statistical dataand the third set of statistical data (as discussed above in detaileddescription of FIG. 1 and FIG. 2). Furthermore, the correlating module314 d correlates the current operational state data with the pastoperational state data associated with the each of the plurality ofenergy consuming devices 104. The current operational state data and thepast operational state data are correlated to determine the potentialfor improvement in energy consumption of each of the plurality of energyconsuming devices 104. In addition, the energy demand control system 122correlate the current energy storage capacity and the past energystorage capacity associated with each of the plurality of energy storageand supply means 106. The current energy storage capacity and the pastenergy storage capacity are correlated to determine the potential forimprovement in charge/discharge cycles and energy storage capacity ofeach of the plurality of energy storage and supply means 106.

The analysis is performed to generate the plurality of statisticalresults associated with the energy consumption of the built environment102 in real time. The plurality of statistical results includes one ormore graphs, one or more charts, one or more tables and one or morestatistical maps of the energy consumption as a function of duration ofthe operations. Further, the plurality of statistical results includesbase-load, variable load, the cost of the operations, energy efficiency,the temperature, humidity and daylight. Furthermore, the plurality ofstatistical results includes the real time occupancy of the plurality ofusers 128 inside the built environment 102 and physical parameters ofeach of the plurality of energy consuming devices 104.

The comparison module 316 compares the energy usage profile associatedwith each of the plurality of energy consuming devices 104. In addition,the comparison module 316 compares the energy usage profile associatedwith each user of the plurality of users 128. Moreover, the comparisonmodule 316 compares the energy usage profile associated with each floorof the built environment 102 and each of the one or more builtenvironments. The comparison module 316 compares the energy usageprofile for segregating each of the one or more built environments basedon surplus and shortage of energy demand and supply corresponding to thebuilt environment of the one or more built environments.

The identification module 318 identifies the set of control strategiesand the key performance indicators. The identification module 318identifies the set of control strategies for regulating the firstplurality of parameters associated with the plurality of energyconsuming devices 104. In addition, the identification module 318identifies the set of control strategies for regulating the secondplurality of parameters associated with the plurality of energy storageand supply means 106. Further, the identification module 318 identifiesthe key performance indicators corresponding to one or more levels ofcontrol associated with the set of control strategies. Theidentification module 318 identifies the key performance indicatorsbased on operating behavior and states of each of the plurality ofenergy consuming devices 104 in real time (as explained above indetailed description of FIG. 1 and FIG. 2).

The prioritizing module 320 prioritize the one or more instructionalcontrol strategies from the set of control strategies affectingoperational behavior and states of a type of energy consuming deviceover one or more types of energy consuming devices. The prioritizingmodule 320 prioritize the one or more instructional control strategiesfor reducing the time-variant energy demand associated with the builtenvironment 102. Moreover, the prioritizing module 320 prioritizes theone or more instructional control strategies to achieve the one or morelevels of control (as discussed above in detailed description of FIG. 1and FIG. 2).

The storage module 322 stores the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical data inthe database 204 a. In addition, the storage module 322 stores the keyperformance indicators, the plurality of statistical results and the logfile having one or more instructional control strategies in the database204 a. The database 204 a is associated with the server 204 of theenergy demand control system 122. Moreover, the storage module 322stores the first set of statistical data, the second set of statisticaldata, the third set of statistical data, the fourth set of statisticaldata and the fifth set of statistical data in real time. In addition,the storage module 322 stores the key performance indicators, theplurality of statistical results and the log file having the one or moreinstructional control strategies in real time.

The updating module 324 updates the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical data inreal time. In addition, the updating module 324 updates the keyperformance indicators, the plurality of statistical results and the logfile having the one or more instructional control strategies in realtime.

The displaying module 326 displays the first set of statistical data,the second set of statistical data, the third set of statistical data,the fourth set of statistical data and the fifth set of statistical dataon the one or more statistical monitoring devices 126 in real time. Inaddition, the displaying module 326 displays the plurality ofstatistical results and the log file having one or more instructionalcontrol strategies on the one or more statistical monitoring devices 126in real time.

FIG. 4A and FIG. 4B illustrate a flow chart 400 for prioritizing one ormore instructional control strategies affecting operational behavior andstates of the plurality of energy consuming devices 104 to reduce thetime-variant energy demand, in accordance with various embodiments ofthe present disclosure. It may be noted that to explain the processsteps of flowchart 400, references will be made to the system elementsof FIG. 1, FIG. 2 and FIG. 3. It may also be noted that the flowchart400 may have lesser or more number of steps.

The flowchart 400 initiates at step 402. Following step 402, at step404, the collection module 302 collects the first set of statisticaldata associated with the plurality of energy consuming devices 104present in the one or more built environments. At step 406, the fetchingmodule 304 fetches the second set of statistical data associated withthe occupancy behavior of the plurality of users 128 present inside eachof the one or more built environments. At step 408, the accumulationmodule 306 accumulates the third set of statistical data associated witheach of the plurality of energy storage and supply means 106. At step410, the reception module 308 receives the fourth set of statisticaldata associated with each of the plurality of environmental sensors 118.Further at step 412, the gathering module 310 gathers the fifth set ofstatistical data associated with each of the plurality of energy pricingmodels 120. The flowchart 400 continues from step 414 as shown in FIG.4B. At step 414, the parsing module 312 parses the first set ofstatistical data, the second set of statistical data, the third set ofstatistical data, the fourth set of statistical data and the fifth setof statistical data by developing the energy usage profile. Further atstep 416, the comparison module 316 compare the energy usage profileassociated with each of the plurality of energy consuming devices 104,each user of the plurality of users 128, each floor of a builtenvironment and each of the one or more built environments. At step 418,the identification module 318 identifies the set of control strategiesand the key performance indicators. At step 420, the prioritizing module320 prioritize the one or more instructional control strategies from theset of control strategies affecting the operational behavior and statesof a type of energy consuming device over one or more types of energyconsuming devices 104. Further, the flow chart 400 terminates at step422.

FIG. 5 illustrates a block diagram of a computing device 500, inaccordance with various embodiments of the present disclosure. Thecomputing device 500 includes a bus 502 that directly or indirectlycouples the following devices: memory 504, one or more processors 506,one or more presentation components 508, one or more input/output (I/O)ports 510, one or more input/output components 512, and an illustrativepower supply 514. The bus 502 represents what may be one or more busses(such as an address bus, data bus, or combination thereof). Although thevarious blocks of FIG. 5 are shown with lines for the sake of clarity,in reality, delineating various components is not so clear, andmetaphorically, the lines would more accurately be grey and fuzzy. Forexample, one may consider a presentation component such as a displaydevice to be an I/O component. Also, processors have memory. Theinventors recognize that such is the nature of the art, and reiteratethat the diagram of FIG. 5 is merely illustrative of an exemplarycomputing device 500 that can be used in connection with one or moreembodiments of the present invention. Distinction is not made betweensuch categories as “workstation,” “server,” “laptop,” “hand-helddevice,” etc., as all are contemplated within the scope of FIG. 5 andreference to “computing device.” The computing device 500 typicallyincludes a variety of computer-readable media. The computer-readablemedia can be any available media that can be accessed by the computingdevice 500 and includes both volatile and nonvolatile media, removableand non-removable media. By way of example, and not limitation, thecomputer-readable media may comprise computer storage media andcommunication media. The computer storage media includes volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information such as computer-readableinstructions, data structures, program modules or other data. Thecomputer storage media includes, but is not limited to, RAM, ROM,EEPROM, flash memory or other memory technology, CD-ROM, digitalversatile disks (DVD) or other optical disk storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or any other medium which can be used to store the desired informationand which can be accessed by the computing device 500. The communicationmedia typically embodies computer-readable instructions, datastructures, program modules or other data in a modulated data signalsuch as a carrier wave or other transport mechanism and includes anyinformation delivery media. The term “modulated data signal” means asignal that has one or more of its characteristics set or changed insuch a manner as to encode information in the signal. By way of example,and not limitation, communication media includes wired media such as awired network or direct-wired connection, and wireless media such asacoustic, RF, infrared and other wireless media. Combinations of any ofthe above should also be included within the scope of computer-readablemedia.

Memory 504 includes computer-storage media in the form of volatileand/or nonvolatile memory. The memory 504 may be removable,non-removable, or a combination thereof. Exemplary hardware devicesinclude solid-state memory, hard drives, optical-disc drives, etc. Thecomputing device 500 includes one or more processors that read data fromvarious entities such as memory 504 or I/O components 512. The one ormore presentation components 508 present data indications to a user orother device. Exemplary presentation components include a displaydevice, speaker, printing component, vibrating component, etc. The oneor more I/O ports 510 allow the computing device 500 to be logicallycoupled to other devices including the one or more I/O components 512,some of which may be built in. Illustrative components include amicrophone, joystick, game pad, satellite dish, scanner, printer,wireless device, etc.

The present disclosure has many advantages over the existing art. Thepresent disclosure provides technical advantages, economic advantages aswell as ancillary benefits. The present disclosure enables theutilization of the energy storage and supply means having relativelysmaller size and energy storage capacity for addressing the sametime-variant load reduction requirements. In addition, the presentdisclosure controls a large amount of energy loads or demands and costassociated with the installation and operations. Moreover, the presentdisclosure provides a stable grid network resulting in stable energypricing and removing volatility of current power system designs.

The foregoing descriptions of specific embodiments of the presenttechnology have been presented for purposes of illustration anddescription. They are not intended to be exhaustive or to limit thepresent technology to the precise forms disclosed, and obviously manymodifications and variations are possible in light of the aboveteaching. The embodiments were chosen and described in order to bestexplain the principles of the present technology and its practicalapplication, to thereby enable others skilled in the art to best utilizethe present technology and various embodiments with variousmodifications as are suited to the particular use contemplated. It isunderstood that various omissions and substitutions of equivalents arecontemplated as circumstance may suggest or render expedient, but suchare intended to cover the application or implementation withoutdeparting from the spirit or scope of the claims of the presenttechnology.

While several possible embodiments of the invention have been describedabove and illustrated in some cases, it should be interpreted andunderstood as to have been presented only by way of illustration andexample, but not by limitation. Thus, the breadth and scope of apreferred embodiment should not be limited by any of the above-describedexemplary embodiments.

What is claimed is:
 1. A method for managing energy consumption,comprising: collecting, at an energy demand control system with aprocessor, a first set of statistical data associated with an energyconsumption of a plurality of energy consuming devices; fetching, at theenergy demand control system, a second set of statistical dataassociated with an occupancy behavior of a plurality of users;accumulating, at the energy demand control system, a third set ofstatistical data associated with each of a plurality of energy storageand supply devices or systems, wherein the third set of statistical datacomprises a current and historical energy storage and supply capacitydata associated with the plurality of energy storage and supply devicesor systems; receiving, at the energy demand control system, a fourth setof statistical data associated with each of a plurality of environmentalsensors, wherein the fourth set of statistical data comprises a currentand historical environmental condition data; gathering, at the energydemand control system, a fifth set of statistical data associated witheach of a plurality of energy pricing models, wherein the fifth set ofstatistical data comprises current and historical recordings of energypricing state affecting the one or more built environments; parsing, atthe energy demand control system, the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical data bydeveloping an energy usage profile of each category of energy consumingdevices, each user of the plurality of users, and each floor of one ormore built environments; comparing, at the energy demand control system,the energy usage profile associated with each of the plurality of energyconsuming devices, each user of the plurality of users, and each floorof the built environment, wherein the comparison being performed forsegregating each of the one or more built environments based on surplusand shortage of energy demand and supply corresponding to the builtenvironment of the one or more built environments; identifying, at theenergy demand control system, a set of control strategies and keyperformance indicators, wherein the set of control strategies beingidentified for regulating a first plurality of parameters associatedwith the plurality of energy consuming devices and a second plurality ofparameters associated with the plurality of energy storage and supplydevices or systems, wherein the key performance indicators beingidentified corresponding to one or more levels of control associatedwith the set of control strategies, wherein the key performanceindicators being identified based on operating behavior and states ofeach of the plurality of energy consuming devices; and prioritizing, atthe energy demand control system, the one or more control strategiesfrom the set of control strategies affecting operational behavior andstates of a type of energy consuming device over one or more types ofenergy consuming devices for reducing the time-variant energy demand,wherein the one or more control strategies being prioritized to achievethe one or more levels of control.
 2. The method of claim 1, wherein thefirst set of statistical data comprises a current operational state dataand a past operational state data associated with the plurality ofenergy consuming devices.
 3. The method of claim 1, wherein the firstset of statistical data is gathered by one or more energy meteringdevices installed in each of the one or more built environments.
 4. Themethod of claim 1, wherein the first set of statistical data is gatheredbased on a first plurality of parameters.
 5. The method of claim 1,wherein the second set of statistical data comprises a first pluralityof occupancy data and a second plurality of occupancy data, wherein thefirst plurality of occupancy data being associated with energyconsumption behavior of each of the plurality of users and the secondplurality of occupancy data being associated with an occupancy patternof each of the plurality of users present inside the one or more builtenvironments.
 6. The method of claim 1, wherein the third set ofstatistical data is accumulated based on a second plurality ofparameters.
 7. The method of claim 1, wherein the fourth set ofstatistical data is received based on a third plurality of parameters.8. The method of claim 1, wherein the fifth set of statistical data isgathered based on a fourth plurality of parameters.
 9. The method ofclaim 1, wherein the set of control strategies comprises a plurality ofoperational and non-operational instructions.
 10. The method of claim 1,wherein the one or more instructional control strategies beingidentified and prioritized based on the comparison of the energy usageprofile associated with each of the plurality of energy consumingdevices, each occupant of the plurality of users, each floor of the oneor more built environment and the key performance indicators associatedwith each of the plurality of energy consuming devices.
 11. The methodof claim 1, wherein the set of control strategies being prioritizedagainst the occupancy pattern of the plurality of users, the energyconsumption behavior of the plurality of users present inside the one ormore built environments, comfort level of each of the plurality ofusers, environmental conditions associated with the one or more builtenvironments, weather forecasts and the energy pricing state associatedwith the one or more built environments.
 12. The method of claim 1,wherein the plurality of operational and non-operational instructionscomprises at least one of the following: regulating power supply of eachof the plurality of energy consuming devices based on an occupancypattern, energy demand and architectural design of the one or more builtenvironments; regulating energy consumption duration of the plurality ofenergy consuming devices; performing an operation on the plurality ofenergy consuming devices, the operation being selected from a group ofoperations consisting of upgrading, downgrading, replacing and repairingof the plurality of energy consuming devices; prompting the plurality ofenergy storage and supply devices or systems to start and stop chargecycles at specific time periods for reducing energy consumption costs;prompting the plurality of energy storage and supply devices or systemsto start and stop discharge cycles for controlling peak loading periods;and regulating charging and discharging characteristics of each of theplurality of energy storage and supply devices or systems.
 13. Themethod of claim 1, further comprising analyzing, at the energy demandcontrol system, the first set of statistical data associated with theplurality of energy consuming devices, the second set of statisticaldata associated with the occupancy behavior of the plurality of users,the third set of statistical data associated with the plurality ofenergy storage and supply devices or systems, the fourth set ofstatistical data associated with the plurality of environmental sensorsand the fifth set of statistical data associated with the plurality ofenergy pricing models, wherein the analyzing being done by performingone or more statistical functions to generate a plurality of statisticalresults.
 14. The method of claim 13, wherein the one or more statisticalfunctions comprises at least one of the following: deriving energydemand values by translating the current operational state data and thepast operational state data associated with the plurality of energyconsuming devices for a pre-defined interval of time; imputing one ormore data entries in the first set of statistical data, the second setof statistical data and the third set of statistical data based on aself-learning algorithm; and correlating the current operational statedata with the past operational state data to determine a potential forimprovement in energy consumption of each of the plurality of energyconsuming devices.
 15. The method of claim 13, wherein the plurality ofstatistical results comprises one or more graphs, one or more charts,one or more tables and one or more statistical maps of energyconsumption as a function of duration of operations of the plurality ofenergy consuming devices, energy storage and supply capacity of theplurality of energy storage and supply devices or systems, occupancy,environmental conditions and energy pricing affecting the one or morebuilt environments.
 16. The method of claim 1, wherein the firstplurality of parameters comprises a set of operational characteristicsassociated with each of the plurality of energy consuming devices and aset of physical characteristics associated with each of the plurality ofenergy consuming devices, wherein the set of operational characteristicscomprises a current rating, a voltage rating, a power rating, afrequency of operation, an operating temperature, a device temperature,the duration of operation, a seasonal variation in operation andoff-seasonal variation in operation and wherein the set of physicalcharacteristics comprises a device size, a device area, a devicephysical location and a portability of device.
 17. The method of claim1, wherein the second plurality of parameters comprises charging anddischarging rates, temperature characteristics, an energy storage andrelease capacity, charge current, charge level, discharge current, idletime and depth of discharge associated with the plurality of energystorage and supply devices or systems.
 18. The method of claim 1,wherein the third plurality of parameters comprises a devices or systemsof recording environmental data comprising temperature, humidity and airpressure associated with each of the plurality of environmental sensorspresent inside or outside the one or more built environments and whereinthe environmental data being obtained from a plurality of externalapplication programming interfaces and a plurality of third partydatabases.
 19. The method of claim 1, wherein the fourth plurality ofparameters comprises a devices or systems of recording energy pricingdata including an energy pricing model or an energy price signalassociated with the one or more built environments and wherein theenergy pricing data being obtained from a plurality of externalapplication programming interfaces and a plurality of third partydatabases.
 20. The method of claim 1, further comprising storing, at theenergy demand control system, the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data, the fifth set of statistical data, thekey performance indicators, plurality of statistical results and a logfile having the plurality of operational and non-operationalinstructions in a database.
 21. The method of claim 1, furthercomprising updating, at the energy demand control system, the first setof statistical data, the second set of statistical data, the third setof statistical data, the fourth set of statistical data, the fifth setof statistical data, the key performance indicators, plurality ofstatistical results and a log file having the plurality of operationaland non-operational instructions.
 22. The method of claim 1, furthercomprising displaying, at the energy demand control system, the firstset of statistical data, the second set of statistical data, the thirdset of statistical data, the fourth set of statistical data, the fifthset of statistical data, the key performance indicators, plurality ofstatistical results and a log file having the plurality of operationaland non-operational instructions, wherein the displaying being providedon one or more statistical monitoring devices.
 23. A energy demandcontrol system comprising: one or more processors; a database configuredto store a first set of statistical data, a second set of statisticaldata, a third set of statistical data, a fourth set of statistical data,a fifth set of statistical data, key performance indicators, a pluralityof statistical results, one or more energy usage profiles and a log filehaving a plurality of operational and non-operational instructions; anda memory coupled to the one or more processors, the memory for storinginstructions which, when executed by the one or more processors, causethe one or more processors to perform a method for prioritizing one ormore instructional control strategies affecting operational behavior andstates of energy consuming devices and reducing time-variant energydemand of the one or more built environments associated with renewableenergy power sources, the method comprising: collecting the first set ofstatistical data associated with an energy consumption of a plurality ofenergy consuming devices; fetching the second set of statistical dataassociated with an occupancy behavior of a plurality of users;accumulating the third set of statistical data associated with each of aplurality of energy storage and supply devices or systems, wherein thethird set of statistical data comprises a current and historical energystorage and supply capacity data associated with the plurality of energystorage and supply devices or systems; receiving the fourth set ofstatistical data associated with each of a plurality of environmentalsensors, wherein the fourth set of statistical data comprises a currentand historical environmental condition data; gathering the fifth set ofstatistical data associated with each of a plurality of energy pricingmodels, wherein the fifth set of statistical data comprises current andhistorical recordings of energy pricing state affecting the one or morebuilt environments; parsing the first set of statistical data, thesecond set of statistical data, the third set of statistical data, thefourth set of statistical data and the fifth set of statistical data bydeveloping an energy usage profile of each category of energy consumingdevices, each user of the plurality of users, and each floor of one ormore built environments; comparing the energy usage profile associatedwith each of the plurality of energy consuming devices, each user of theplurality of users, and each floor of the built environment, wherein thecomparison being performed for segregating each of the one or more builtenvironments based on surplus and shortage of energy demand and supplycorresponding to the built environment of the one or more builtenvironments; identifying a set of control strategies and keyperformance indicators, wherein the set of control strategies beingidentified for regulating a first plurality of parameters associatedwith the plurality of energy consuming devices and a second plurality ofparameters associated with the plurality of energy storage and supplydevices or systems, wherein the key performance indicators beingidentified corresponding to one or more levels of control associatedwith the set of control strategies, wherein the key performanceindicators being identified based on operating behavior and states ofeach of the plurality of energy consuming devices; and prioritizing theone or more control strategies from the set of control strategiesaffecting operational behavior and states of a type of energy consumingdevice over one or more types of energy consuming devices for reducingthe time-variant energy demand, wherein the one or more controlstrategies being prioritized to achieve the one or more levels ofcontrol.
 24. The energy demand control system of claim 23, wherein thefirst set of statistical data comprises a current operational state dataand a past operational state data associated with the plurality ofenergy consuming devices.
 25. The energy demand control system of claim23, further comprising one or more energy metering devices installed ineach of the one or more built environments, and wherein the first set ofstatistical data is gathered by the one or more energy metering devices.26. The energy demand control system of claim 23, wherein the first setof statistical data is gathered based on a first plurality ofparameters.
 27. The energy demand control system of claim 23, whereinthe second set of statistical data comprises a first plurality ofoccupancy data and a second plurality of occupancy data, wherein thefirst plurality of occupancy data being associated with energyconsumption behavior of each of the plurality of users and the secondplurality of occupancy data being associated with an occupancy patternof each of the plurality of users present inside the one or more builtenvironments.
 28. The energy demand control system of claim 23, whereinthe third set of statistical data is accumulated based on a secondplurality of parameters.
 29. The energy demand control system of claim23, wherein the fourth set of statistical data is received based on athird plurality of parameters.
 30. The energy demand control system ofclaim 23, wherein the fifth set of statistical data is gathered based ona fourth plurality of parameters.
 31. The energy demand control systemof claim 23, wherein the set of control strategies comprises a pluralityof operational and non-operational instructions.
 32. The energy demandcontrol system of claim 23, wherein the one or more instructionalcontrol strategies being identified and prioritized based on thecomparison of the energy usage profile associated with each of theplurality of energy consuming devices, each occupant of the plurality ofusers, each floor of the one or more built environment and the keyperformance indicators associated with each of the plurality of energyconsuming devices.
 33. The energy demand control system of claim 23,wherein the set of control strategies being prioritized against theoccupancy pattern of the plurality of users, the energy consumptionbehavior of the plurality of users present inside the one or more builtenvironments, comfort level of each of the plurality of users,environmental conditions associated with the one or more builtenvironments, weather forecasts and the energy pricing state associatedwith the one or more built environments.
 34. The energy demand controlsystem of claim 23, wherein the plurality of operational andnon-operational instructions comprises at least one of the following:regulating power supply of each of the plurality of energy consumingdevices based on an occupancy pattern, energy demand and architecturaldesign of the one or more built environments; regulating energyconsumption duration of the plurality of energy consuming devices;performing an operation on the plurality of energy consuming devices,the operation being selected from a group of operations consisting ofupgrading, downgrading, replacing and repairing of the plurality ofenergy consuming devices; prompting the plurality of energy storage andsupply devices or systems to start and stop charge cycles at specifictime periods for reducing energy consumption costs; prompting theplurality of energy storage and supply devices or systems to start andstop discharge cycles for controlling peak loading periods; andregulating charging and discharging characteristics of each of theplurality of energy storage and supply devices or systems.
 35. Theenergy demand control system of claim 23, wherein the instructions arefurther configured to cause the one or more processors to analyze thefirst set of statistical data associated with the plurality of energyconsuming devices, the second set of statistical data associated withthe occupancy behavior of the plurality of users, the third set ofstatistical data associated with the plurality of energy storage andsupply devices or systems, the fourth set of statistical data associatedwith the plurality of environmental sensors and the fifth set ofstatistical data associated with the plurality of energy pricing models,by performing one or more statistical functions to generate a pluralityof statistical results.
 36. The energy demand control system of claim23, wherein the one or more statistical functions comprises at least oneof the following: deriving energy demand values by translating thecurrent operational state data and the past operational state dataassociated with the plurality of energy consuming devices for apre-defined interval of time; imputing one or more data entries in thefirst set of statistical data, the second set of statistical data andthe third set of statistical data based on a self-learning algorithm;and correlating the current operational state data with the pastoperational state data to determine a potential for improvement inenergy consumption of each of the plurality of energy consuming devices.37. The energy demand control system of claim 36, wherein the pluralityof statistical results comprises one or more graphs, one or more charts,one or more tables and one or more statistical maps of energyconsumption as a function of duration of operations of the plurality ofenergy consuming devices, energy storage and supply capacity of theplurality of energy storage and supply devices or systems, occupancy,environmental conditions and energy pricing affecting the one or morebuilt environments.
 38. The energy demand control system of claim 26,wherein the first plurality of parameters comprises a set of operationalcharacteristics associated with each of the plurality of energyconsuming devices and a set of physical characteristics associated witheach of the plurality of energy consuming devices, wherein the set ofoperational characteristics comprises a current rating, a voltagerating, a power rating, a frequency of operation, an operatingtemperature, a device temperature, the duration of operation, a seasonalvariation in operation and off-seasonal variation in operation andwherein the set of physical characteristics comprises a device size, adevice area, a device physical location and a portability of device. 39.The energy demand control system of claim 28, wherein the secondplurality of parameters comprises charging and discharging rates,temperature characteristics, an energy storage and release capacity,charge current, charge level, discharge current, idle time and depth ofdischarge associated with the plurality of energy storage and supplydevices or systems.
 40. The energy demand control system of claim 29,wherein the third plurality of parameters comprises a devices or systemsof recording environmental data comprising temperature, humidity and airpressure associated with each of the plurality of environmental sensorspresent inside or outside the one or more built environments and whereinthe environmental data being obtained from a plurality of externalapplication programming interfaces and a plurality of third partydatabases.
 41. The energy demand control system of claim 30, wherein thefourth plurality of parameters comprises a devices or systems ofrecording energy pricing data including an energy pricing model or anenergy price signal associated with the one or more built environmentsand wherein the energy pricing data being obtained from a plurality ofexternal application programming interfaces and a plurality of thirdparty databases.
 42. The energy demand control system of claim 23,wherein the instructions are further configured to cause the one or moreprocessors to store the first set of statistical data, the second set ofstatistical data, the third set of statistical data, the fourth set ofstatistical data, the fifth set of statistical data, the key performanceindicators, plurality of statistical results and the log file having theplurality of operational and non-operational instructions in thedatabase.
 43. The energy demand control system of claim 23, wherein theinstructions are further configured to cause the one or more processorsto update the first set of statistical data, the second set ofstatistical data, the third set of statistical data, the fourth set ofstatistical data, the fifth set of statistical data, the key performanceindicators, plurality of statistical results and a log file having theplurality of operational and non-operational instructions.
 44. Theenergy demand control system of claim 23, further comprising one or morestatistical monitoring devices, and wherein the instructions are furtherconfigured to cause the one or more processors to display the first setof statistical data, the second set of statistical data, the third setof statistical data, the fourth set of statistical data, the fifth setof statistical data, the key performance indicators, plurality ofstatistical results and a log file having the plurality of operationaland non-operational instructions on the one or more statisticalmonitoring devices.